I have time-series data that track event occurrence in 3 locations. Here's a sample:
Count Total
Location A B C
Date
2018-06-22 0 1 1 2
2018-06-23 2 1 0 3
2018-06-24 0 0 1 1
2018-06-25 2 2 1 5
2018-06-26 0 3 1 4
I would like to use the data to predict the total number of event occurrences at a given date in the future. How do I test if an event happening in one location has an impact on events happening in another location (dependency)? I believe that if an event happening in locations B and C are dependant, I should sum the 2 columns together as 1 feature in my model.